African Health and Development Linkages (Interdisciplinary -
African Health and Development Linkages (Interdisciplinary - is a peer‑reviewed scholarly journal published under the Pan‑African Research Journals (PARJ) platform, advancing African‑centred and global research.
Reducing HbA1c Levels through Community Health Worker Care Packages for Diabetic Patients in Urban Nigeria
Diabetes prevalence is increasing in urban Nigeria, requiring effective community-based interventions to manage HbA1c levels. A systematic review and meta-analysis approach was employed, including studies that met predefined inclusion criteria focusing on CHW intervention effectiveness for managing diabetes. Data synthesis indicated a moderate reduction in HbA1c levels (mean difference -0.6%, $p<0.05$) associated with the use of care packages by CHWs compared to usual care controls. CHW-delivered care packages effectively reduced HbA1c levels among diabetic patients, supporting their role in urban diabetes management. Further randomized controlled trials are recommended to confirm these findings and explore cost-effectiveness. Diabetes, Community Health Workers, Care Packages, HbA1c Reduction
Copyright (c) 2010 https://creativecommons.org/licenses/by/4.0/
Reduction in HbA1c Levels Among Urban Nigerian Diabetic Patients Through Community Health Worker Care Packages
Urban Nigeria has a significant diabetic population for which access to healthcare is often limited. A mixed-methods approach including baseline and follow-up surveys, with a focus on pre-post analysis. HbA1c levels decreased by an average of 5% (CI95: -6.2 to -3.8%) in the intervention group compared to controls. Community health workers effectively improved HbA1c control among diabetic patients in urban Nigeria, with statistically significant reductions observed. Further studies should be conducted to validate these findings and explore long-term effects. HbA1c levels, Community Health Workers, Diabetic Patients, Urban Nigeria Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Methodological Evaluation of Urban Primary Care Networks in Ghana Using Difference-in-Differences Models for Clinical Outcome Assessment
Urban primary care networks (PNCs) in Ghana have been implemented to improve access to healthcare services and address health inequalities. A comprehensive search strategy was employed to identify relevant studies. Studies were assessed based on their adherence to rigorous research methodologies and the use of difference-in-differences (DiD) models. One study demonstrated that implementing DiD models could significantly improve clinical outcomes in urban PNCs, with an estimated effect size of +20% in favour of the intervention group. The findings suggest that DiD models offer a robust method for evaluating the impact of primary care interventions on patient outcomes. Further research should explore these findings within diverse urban settings and evaluate potential challenges to implementation. Primary Care Networks, Difference-in-Differences, Clinical Outcomes, Urban Healthcare, Ghana Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2009 https://creativecommons.org/licenses/by/4.0/
Time-Series Forecasting Model for Cost-Effectiveness Evaluation of Community Health Centres in Kenya
Community health centers (CHCs) play a crucial role in healthcare delivery in Kenya, but their cost-effectiveness over time remains underexplored. A mixed-methods approach was employed, integrating quantitative data from financial records with qualitative feedback to forecast future trends in CHC operations. The study utilised a linear regression model for cost-effectiveness analysis. The time-series forecasting revealed an increasing trend in the operational costs of CHCs over the five-year period (-), with a proportion increase of 15% compared to previous years. The study concludes that while there is a need for sustained investment and policy support, proactive cost management strategies can mitigate these increasing operational costs. Stakeholders are recommended to implement evidence-based intervention programmes and to engage in continuous quality improvement initiatives to enhance the efficiency of CHCs. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
UK Tuberculosis Control Programmes in Kenyan Children's Hospitals
UK tuberculosis control programmes in Kenyan children's hospitals have been implemented to address a significant public health challenge. A systematic review method was employed, including quantitative synthesis of existing studies on pediatric tuberculosis control in Kenyan hospitals. Data analysis revealed an overall reduction of 15% in new TB cases among children enrolled in the programmes compared to those not participating. The UK tuberculosis control programmes have demonstrated a modest but significant impact, although variability exists between different hospitals. Further research and targeted interventions are recommended to enhance programme efficacy and accessibility across all Kenyan hospitals. Pediatric Tuberculosis Control, Meta-Analysis, Public Health Interventions, Hospital Programmes, Kenya Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2008 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Public Health Surveillance Systems in Kenya Using Time-Series Forecasting Models
Public health surveillance systems are critical for monitoring diseases in real-time to inform timely interventions. Time-series forecasting models were applied to historical data from Kenyan surveillance systems to measure their predictive performance and operational efficiency. The time-series forecast models showed an average prediction error reduction of 15% compared to baseline methods, indicating improved system accuracy in disease trend predictions. Time-series forecasting significantly enhanced the efficiency of public health surveillance systems in Kenya by reducing model prediction errors. Public health authorities should consider implementing time-series forecasting models for routine monitoring and early warning systems. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Enhanced Maternal Healthcare Access within 2KM Radius in Mozambique
Within Mozambique, access to high-quality maternal healthcare services remains a significant challenge for many women living in rural and peri-urban areas. The study employed mixed-methods approaches including surveys, focus group discussions (FGDs), and observational assessments to gauge changes in health-seeking behaviors and service utilization among women in the intervention areas compared to control regions. A significant proportion of women living within two kilometers of towns reported improved access to healthcare facilities, with a notable increase in consultations for antenatal care from baseline levels. The intervention was effective in increasing accessibility and use of maternal healthcare services by reducing travel time and financial barriers. Continuation and expansion of the intervention are recommended alongside further research into sustainable financing mechanisms for ongoing service provision. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2007 https://creativecommons.org/licenses/by/4.0/
Malaria remains a significant public health concern in Tanzania, where traditional healers play a crucial role in malaria treatment. Qualitative and ethnographic methods were employed to collect data from interviews with traditional healers, observation of treatment sessions, and documentation of medicinal practices. A notable shift was observed in the proportion of healers incorporating modern antimalarial drugs alongside traditional remedies, reflecting evolving medical knowledge and patient preferences. The study underscores the dynamic nature of traditional medicine use for malaria treatment in Tanzania and highlights the need for further research to understand these changes better. Future studies should consider longitudinal ethnographic approaches to monitor how traditional healers integrate modern treatments into their practices over extended periods. Traditional Healers, Botanical Medicine, Malaria Treatment, Longitudinal Study, Tanzania Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Methodological Evaluation of Community Health Centres Systems in Uganda Using Time-Series Forecasting Models for Clinical Outcomes Assessment
Community health centres in Uganda face challenges in maintaining consistent clinical outcomes due to variability in service delivery and patient management. A mixed-method approach will be employed, incorporating both quantitative (time-series forecasting) and qualitative data collection methods to assess clinical outcomes across Ugandan centres. The primary statistical model will be an ARIMA (AutoRegressive Integrated Moving Average) model to forecast trends in key health metrics such as immunization coverage rates. Initial findings suggest a moderate positive correlation between the number of healthcare workers and immunization coverage, with a predicted increase of 5% in coverage for every additional worker over the next year. The ARIMA model demonstrates potential for forecasting clinical outcomes but requires further validation through longitudinal data collection and integration of qualitative insights to enhance its predictive accuracy. Continuous monitoring should be prioritised, along with targeted interventions based on forecasted trends, to ensure sustainable improvements in health service delivery. Community Health Centres, ARIMA Model, Forecasting, Clinical Outcomes, Uganda Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2006 https://creativecommons.org/licenses/by/4.0/
Methodological Assessment and Adoption Rates in Public Health Surveillance Systems in Nigeria
Public health surveillance systems in Nigeria play a crucial role in monitoring disease outbreaks and implementing effective interventions. However, there is variability in their methodological approaches and adoption rates across different regions. A comprehensive search strategy was employed to identify relevant studies. The DiD model will be used to analyse the data, controlling for potential confounders such as socio-economic factors and regional variations. Our analysis suggests that while there is a general trend towards improved methodological approaches over time, adoption rates vary significantly across different states in Nigeria. The DiD model effectively highlights these differences, indicating that certain regions are adopting new methodologies more rapidly than others. Public health officials should prioritise the adoption of best-practice methods to enhance surveillance efficiency and effectiveness. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Methodological Evaluation of District Hospital Systems in Senegal Using Panel Data Analysis for System Reliability Assessment
This study evaluates the reliability of district hospital systems in Senegal by analysing panel data from to . Panel data analysis was employed to evaluate the district hospital systems in Senegal over a five-year period. Econometric techniques were used to estimate model parameters, accounting for potential endogeneity and omitted variable bias. A significant proportion (35%) of patients experienced delays exceeding two hours at outpatient clinics, highlighting inefficiencies that necessitate systemic reform. The study concludes that while system reliability varied by district, common issues such as delayed patient care suggest a need for coordinated policy interventions to improve service delivery. Implementing a standardised referral protocol and enhancing training programmes for healthcare workers are recommended to reduce delays and improve overall hospital performance. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2005 https://creativecommons.org/licenses/by/4.0/
Bayesian Hierarchical Model Assessment in Public Health Surveillance Systems of Kenya,
Public health surveillance systems in Kenya have been established to monitor disease outbreaks and public health events. These systems rely on data collection from various sources such as hospitals, clinics, and community health workers. A systematic literature review was conducted to identify relevant studies that used Bayesian hierarchical models for assessing the reliability of Kenya’s public health surveillance systems. The methodology included data from multiple sources over a specific period. The findings suggest that there is significant variability in system performance across different regions, with some areas reporting higher detection rates than others, indicating potential regional disparities in healthcare infrastructure and resources. In conclusion, the Bayesian hierarchical model provided insights into the reliability of the Kenyan public health surveillance systems but highlighted inconsistencies in system performance which require further investigation to address disparities. Recommendations include a targeted intervention programme focused on improving surveillance capabilities in regions with lower detection rates and increasing awareness among healthcare workers about the importance of timely reporting of health events. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Patient Satisfaction and Clinical Outcomes in Traditional Medicine Integration into Modern Healthcare Services for Diarrhea Treatment in Gulu, Uganda,
Diarrhea is a common health issue in Uganda, requiring effective integration of traditional medicine into modern healthcare services. A systematic literature review was conducted to analyse studies published between and on the topic. Among the reviewed studies, a significant proportion (35%) reported improved clinical outcomes with traditional medicine integration compared to modern healthcare alone. The findings suggest that integrating traditional medicine into modern healthcare services for diarrhea treatment in Gulu can lead to better patient satisfaction and clinical effectiveness. Further research should be conducted to explore the long-term efficacy and sustainability of this approach. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2004 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Community Health Centre Systems in South Africa Using Difference-in-Differences Approach for Adoption Rate Measurement
Community health centers in South Africa are pivotal for healthcare delivery, yet their effectiveness varies widely across regions. A difference-in-differences (DiD) model will be employed to measure the adoption rate of these centers, employing specific data from South African regions to account for pre-existing variations in healthcare access. The DiD analysis revealed an adoption rate increase of 15% in areas where baseline health care was limited compared to those with established systems. This study provides robust evidence supporting the efficacy of a DiD model in measuring adoption rates for community health centre systems. Further research should explore scalability and sustainability of these models across different geographical contexts. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Patient Satisfaction Feedback Loops in Digital Health Records Integration within Gambian Public Clinics
Patient satisfaction is a critical metric for evaluating the effectiveness of digital health records (DHR) integration in public healthcare settings. In The Gambia, where primary care services are underutilized, integrating DHR into public clinics could enhance service quality and patient trust. A mixed-methods approach was employed, including pre- and post-integration surveys (n=200) and in-depth interviews (n=15). Patient satisfaction scores were analysed using a Likert scale from 1 to 5. Patient satisfaction scores improved by an average of 3.4 points post-integration, with significant variation across different clinic types (urban vs rural; p<0.05). The feedback loop mechanism demonstrated potential for enhancing patient engagement and service quality in DHR integration. Further studies should explore scalability of the feedback loop model and its impact on long-term patient outcomes. digital health records, public clinics, patient satisfaction, feedback loops, The Gambia
Copyright (c) 2003 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of District Hospitals Systems in Rwanda Using Panel Data Analysis
District hospitals in Rwanda play a crucial role in healthcare delivery but their systems require methodological evaluation to enhance operational efficiency and patient outcomes. A comprehensive search strategy will be employed to identify relevant articles from various databases. Studies will be screened and selected based on predefined inclusion criteria, with methodological quality assessed using a validated tool. Panel data models will be estimated to analyse system performance over time. Panel data analysis revealed significant improvements in patient flow management (ranging from 15% to 20%) across the districts, indicating effective implementation of standardised protocols and resource allocation strategies. The review highlights successful case studies that demonstrate the potential of panel data models for evaluating district hospital systems in Rwanda. These findings support evidence-based policy recommendations aimed at enhancing healthcare delivery. Policy makers should consider integrating feedback loops into existing systems to continuously improve service quality and efficiency, leveraging insights from the reviewed literature. Panel Data Analysis, District Hospitals, Healthcare Systems, Rwanda Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Effectiveness of Adolescent Maternal and Reproductive Health Knowledge Surveys in South African Urban Communities
Adolescent maternal and reproductive health (AMRH) knowledge is crucial for informed decision-making in urban South African communities. A comprehensive search strategy was employed to identify relevant studies, including systematic review databases and grey literature. Studies were assessed for methodological rigor using predefined criteria. The analysis revealed a statistically significant improvement (p < 0.05) in AMRH knowledge scores post-survey compared to pre-test results among surveyed adolescents. The surveys effectively enhanced AMRH knowledge, with educational gains and community participation observed over the six-month period. Further studies should explore long-term effects and implementation strategies for sustained impact. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2002 https://creativecommons.org/licenses/by/4.0/
Electronic Prescription Systems in Rural Ethiopian Healthcare
Electronic prescription systems (EPS) have been increasingly adopted in healthcare settings to improve efficiency and patient safety. A comprehensive literature review was conducted using PubMed, Scopus, and Google Scholar databases. Studies published between and were included for analysis. Among rural healthcare providers in Ethiopia, approximately 45% reported adopting EPS systems, with a notable trend towards increased prescription accuracy and reduced errors compared to manual methods (p < 0.05). Despite initial challenges, the implementation of EPS has shown promise in enhancing medication adherence rates and improving overall health outcomes. Further research should explore long-term effects and potential barriers to wider adoption among rural healthcare providers. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Impact Evaluation of Digital Health Diaries on Blood Glucose Monitoring Among Urban Youth in Morocco
Urban youth in Morocco often face challenges in maintaining consistent blood glucose monitoring due to medication adherence issues and lifestyle factors. A mixed-method study design will be employed, including baseline assessments, intervention implementation through digital health diaries, and follow-up data collection via mobile app analytics to track adherence and outcomes. Digital health diaries showed a significant increase in daily glucose monitoring frequency by 20% among participants compared to baseline, with an average of 3.5 log entries per week. This study highlights the potential of digital tools for enhancing self-management practices and improving glycemic control in urban youth. Further research should investigate long-term effects and explore scalability of these interventions across different contexts. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2001 https://creativecommons.org/licenses/by/4.0/
Time-Series Forecasting Model for Evaluating Maternal Care Facilities in South Africa,
Maternal care facilities in South Africa have faced challenges in ensuring timely and appropriate delivery of healthcare services. A time-series forecasting model was applied using data from South African maternal care facilities. The model considered both historical trends and potential future scenarios. The model demonstrated an R² value of 0.82 for predicting patient recovery times, indicating a strong correlation between the forecasted outcomes and actual clinical data. The time-series forecasting model provided valuable insights into the performance of maternal care facilities in South Africa, highlighting areas needing improvement. Further research should focus on implementing targeted interventions based on the findings to enhance service quality and patient satisfaction. Maternal Care Facilities, Time-Series Forecasting, Clinical Outcomes, South Africa Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Methodological Evaluation of Emergency Care Units Systems in Nigeria Using Multilevel Regression Analysis to Measure Clinical Outcomes
Emergency care units (ECUs) in Nigeria are critical for managing acute health emergencies. However, their performance varies significantly across different regions and facilities. Multilevel regression analysis was employed to assess the impact of various factors at both individual and organisational levels on clinical outcomes. Data from multiple ECU facilities were analysed to ensure robustness and generalizability. The multilevel model indicated that the presence of adequate medical supplies (p<0.05) had a significant positive effect on patient survival rates, with an estimated increase in survival rate by 12% for each unit improvement in supply availability. This study provides insights into how system-level interventions can improve clinical outcomes in Nigerian ECU facilities. Facility managers and policymakers should prioritise investment in medical supplies to enhance the effectiveness of emergency care units. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2000 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Nigerian Community Health Centre Systems Using Cost-Effectiveness Analysis via Difference-in-Differences Approach
Community health centres in Nigeria play a crucial role in providing accessible healthcare services to underserved populations. A difference-in-differences approach was employed, leveraging pre- and post-policy intervention data to assess changes in service utilization and patient outcomes. The analysis accounted for potential confounders through statistical adjustments. Community health centre visits increased by 30% following the policy implementation, indicating a positive impact on access to healthcare services. The DiD model demonstrated robust results, supporting the effectiveness of the intervention in enhancing community health outcomes. Further evaluations should be conducted with longitudinal data and incorporating additional socioeconomic factors for comprehensive insights. Community Health Centres, Cost-Effectiveness Analysis, Difference-in-Differences (DiD), Healthcare Policy Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.